主讲人: Yueyue Fan, Associate Professor in Civil and Environmental Engineering at UC Davis
题目：Traffic Network Observability and Stochastic Estimation
报告内容： In this talk, I will discuss a general network identification problem, its special applications in transportation, and how optimization approaches may be applied in this problem context. The general problem is defined as: how can one infer global network parameters (y) based on data measured on local parameters (x), with the relation between x and y built on complex network structure? A familiar example of such problem in transportation is origin-destination (O-D) matrix estimation based on link traffic counts. With more traffic data becoming available through advanced information technologies, we face great opportunities as well as challenges in utilizing the data. In this talk, I will show how optimization could be used to address two challenging issues: (1) how to ensure solution uniqueness through input selection; and (2) how to cope with data uncertainty and integrate heterogeneous data sources via stochastic optimization.
主讲人简介：Dr. Fan is currently an associate professor in Civil and Environmental Engineering at University of California, Davis. She is also affiliated with the graduate programs in Applied Mathematics and Transportation Technologies and Policy. She received her PhD in Civil Engineering at University of Southern California in 2003. Dr. Fan’s research is on transportation and energy infrastructure systems modeling, with special interest in integrating applied mathematics and engineering domain knowledge to address challenges brought by system uncertainty, dynamics, and indeterminacy issues.